34 results about "Chan's algorithm" patented technology

The invention discloses a time division-synchronization code division multiple access (TD-SCDMA) system-based method for accurately positioning underground personnel. The method comprises the following steps of acquiring time of arrival (TOA) and an angle of arrival (AOA) of a signal at a base station; de-noising a TOA value by using an improved kalman filtering algorithm; calculating a time difference of arrival (TDOA) value according to the de-noised TOA value; estimating the position of a mobile station by using a TDOA/AOA mixed Chan algorithm and a TDOA/AOA mixed Taylor algorithm; performing first data fusion on a position estimated value by using a weighted residual method to obtain a new position estimated value; and performing second data fusion on the position estimated value by using Bayesian inference to obtain the final position estimated value. By the method for accurately positioning the underground personnel, the advantages of a TD-SCDMA system and the superiority of the data fusion are utilized, a TDOA/AOA mixed data fusion positioning algorithm is adopted, the positioning accuracy is high, and the problem that the personnel in an underground coal mine are hard to position is solved.

The invention discloses a rapid positioning method based on TDOA (Time Difference Of Arrival), mainly aiming to solve the problems when a tested target performs position solution depending on TDOA detected by a plurality of signal receivers under near and long distance scenes. The method mainly comprises the steps of: coordinate and distance equation establishment, centre distance solution, object coordinate solution, distance constraint and spherical surface relation constraint establishment, and solution of object coordinate corrected solution. The method can solve the problem of passive detection and positioning of an underwater vehicle, and can also be used for solving other positioning problems based on TDOA, such as radio positioning, ultrasonic wave positioning, indoor positioning, etc. Compared with a commonly used Chan algorithm, the rapid positioning method based on TDOA solves the problem of inconformity of near distance and long distance algorithms and existence of fuzzy solution, and furthermore improves precision and stability; compared with a Taylor algorithm, the rapid positioning method based on TDOA does not need external initial value and recursion operation, substantially reduces arithmetic labor, but does not change precision and stability.

The invention provides a real-time high-precision position solution method for a multilateration system. The position solution method comprises the following steps: (1) storing far-end unit information to a buffer memory by using a central processing unit of the multilateration system, judging consistency of time labels and screening effective information; (2) processing the effective information by using the Chan algorithm and calculating a target initial positioning value; (3) substituting the target initial positioning value into the Taylor series expansion method and carrying out recursive operation so as to obtain high-precision positioning information; and (4) subjecting the positioning information to filtering processing by using the self-adaptive Kalman filtering algorithm and reporting the processed positioning information to a display and control system or command system. The position solution method provided by the invention has obviously improved instantaneity and solution precision compared with traditional methods and carries out target positioning through combination of a plurality of algorithms, so requirements on hardware of the central processing unit and on the number of far-end units are lowered down, and cost for hardware in the system is reduced.

The invention discloses an anti-NLoS error locating method based on location unit quality and multi-algorithm data fusion. The method comprises the following steps that a terminal to be detected acquires measuring values fed back by N anchor nodes, the measuring values comprise TOA, RSSI and signal noise ratio (SNR); a Kalman filter is used for processing the TOA measuring values, new TOA measuring values are obtained, the obtained TOA measuring values are divided into two groups, namely second TOA measuring values and TDOA measuring values; a mode searching method and a CHAN algorithm are used for carrying out location computing on the second TOA measuring values and the TDOA measuring values respectively; the weight value of a location unit is determined, the location results of the second TOA measuring values and the TDOA measuring values are respectively subjected to data fusion; the fusion location results of the second TOA measuring values and the fusion location results of the TDOA measuring values are subjected to fusion. According to the method, various kinds of information brought by the measuring values are fully used, integration is carried out through a data fusion method, and accurate location results can be obtained.

The invention relates to a multi-base station secondary positioning method based on a toughness estimation and arrival time difference, belonging to the technical field of wireless positioning. The multi-base station secondary positioning method is characterized by comprising the following steps of: firstly dividing multiple base stations around a mobile table into CN3 combinations in a triplet way; then carrying out primary positioning on the mobile table by adopting a three-base station CHAN algorithm and utilizing the TDOA information of three base stations of each combination so as to generate CN3 positioning results; then carrying out the toughness estimation on the CN3 positioning results so as to obtain a coarse positioning result; and finally carrying out secondary accurate positioning on an object to be positioned by utilizing the TDOA information of three base stations which are in nearest distance with the coarse positioning result. The multi-base station secondary positioning method can not only utilize the TDOA information of the multiple base stations, but also restrain the influence of TDOA values with larger errors on the positioning results, and can also effectively solve the problem that property is fast deteriorated when TDOA estimation errors are larger due to signal attenuation in the traditional CHAN algorithm when the environmental noise is heavier.

The invention discloses a UWB positioning method based on a KF algorithm, a Chan algorithm and a Taylor algorithm. The method includes the following steps: step 1, setting a to-be-detected tag on a to-be-detected carrier, and carrying out fitting processing for distance from to-be-detected tag to each base station in an environment of the four positioning base stations; step 2, using distance values of the step 1 after real-time fitting as measurement values of Kalman filtering to carry out Kalman filtering to obtain distance values after filtering; step 3, using the Chan algorithm on the distance values of the step 2 after Kalman filtering to obtain estimation positions of the to-be-detected tag; and step 4, using the estimation positions, which are of the to-be-detected tag and are calculated by the Chan algorithm in the step 3, as initial values of the Taylor algorithm, and carrying out Taylor algorithm calculation to obtain final estimation positions of the to-be-detected tag. According to the method, linear fitting equations are established for the distance from the to-be-detected tag to each base station, Kalman filtering processing is carried out on results after filtering,non-line-of-sight errors are reduced, ranging results are enabled to be stable and closer to true values, and positioning accuracy is improved.

The embodiment of the invention provides a positioning method and device, electronic equipment and a readable storage medium. The method is applied to the technical field of wireless positioning. Themethod comprises the following steps of: respectively calculating a difference value between the time when the signal transmitted by each measurement base station reaches the mobile terminal and the time when the signal transmitted by the reference base station reaches the mobile terminal; obtaining each TDOA value; according to the three-dimensional position coordinates of each measurement base station and the reference base station, judging whether the heights between the measurement base stations and between the measurement base stations and the reference base station are the same or not; if yes, measuring the height value of the mobile terminal through air pressure; and taking the height value as a position coordinate of one dimension in the three-dimensional position coordinates of the mobile terminal, and solving the position coordinates of other two dimensions of the mobile terminal through a preset 2.5-dimensional Chan algorithm according to the three-dimensional position coordinates of each measurement base station and the reference base station, each TDOA value, the light speed and the position coordinate of one dimension. The positioning range can be enlarged, and the positioning precision is improved.

The present invention relates to a communication base station-based three-dimensional positioning tracking and trajectory calculation method. According to the prior art, a positioning result is an estimated value, the positioning result is not accurate, and as a result, the operation trajectory of a terminal cannot be calculated, while, with the method of the invention adopted, the above situation in the prior art can be avoided. According to the communication base station-based three-dimensional positioning tracking and trajectory calculation method, three-dimensional indoor coarse positioning is performed according to a CHAN algorithm, so that base station acquisition TOA data are obtained; the TOA data are preprocessed; a base station weighted voting value estimation model is established; a measurement value split model is established, so that a real time delay model, a noise time delay model and an interference time delay model can be obtained through splitting; a machine learning measurement fine-tuning model, and a precise multi-point three-dimensional positioning model are established; a precise three-dimensional positioning optimization model is established; and the precise three-dimensional positioning optimization model is applied to the precise multi-point three-dimensional positioning model, and an improved terminal movement trajectory positioning model can be built, so that the trajectory positioning of a moving terminal is completed. With the method provided by the technical schemes of the invention adopted, problems in the prior art can be solved. The communication base station-based three-dimensional positioning tracking and trajectory calculation method can be applied to the tracking and trajectory calculation of indoor three-dimensional positioning.

The invention discloses a multiple-input-multiple-output radar near-field positioning algorithm which includes the steps: firstly, performing estimation of a first weighted least square method by the aid of thinking of a chan algorithm; secondly, defining a new residual matrix, and performing estimation of a second weighted least square method; finally, substituting a result initial value of second estimation into a Taylor algorithm, performing iterative processing until an outputted positioning result is smaller than a minimum set threshold value. According to the positioning algorithm, near-field targets can be accurately positioned, and the positioning algorithm is applicable to multiple-input-multiple-output radar near-field positioning systems.

The invention discloses a fish ultrasonic wave marker precise positioning method and system suitable for a complex water environment. The method comprises the steps of S1, collecting the time when a signal marker fish arrives at each hydrophone in a hydrophone monitoring network or the time difference between arrivals at two hydrophones; S2, estimating approximate coordinates and a signal emissiontime of the signal marker fish by using a Chan algorithm; S3, taking the approximate coordinates of the signal marker fish as the center, constructing an approximate coordinate alternative interval,and dividing the approximate coordinate alternative interval into sub-nets; S4, taking a node position of one subnet as a position initial value of the signal marker fish, and carrying out the signalmarker positioning calculation by using the robust least-square estimation; and S5, evaluating a positioning calculation result obtained in the step S4, if the evaluation passes, determining the position calculation result as the precise positioning result of the signal marker fish, and otherwise, repeating the step S4. The method of the invention can effectively realize the accurate capture of fish movement trajectories with high precision and high reliability.

The invention discloses a three-dimensional UWB indoor positioning method based on an improved CHAN algorithm. The three-dimensional UWB indoor positioning method based on the improved CHAN algorithmcomprises the following steps: receiving a UWB positioning signal sent by a to-be-measured label carried by a to-be-measured object, and obtaining an arrival time parameter and a received signal intensity parameter of each positioning base station for receiving the UWB positioning signal; comparing the received signal strength parameters of each positioning base station, arranging the received signal strength parameters from large to small, and obtaining a second number of positioning base stations of which the received signal strength parameters are arranged in front; respectively obtaining arrival time parameters of a second number of positioning base stations, and determining the distance from each second number of positioning base stations to the to-be-measured label; calculating the distance difference rif between the to-be-measured label and each of the second number of positioning base stations and the to-be-measured label and the reference base station; and obtaining a distancedifference, and obtaining an estimated position of the to-be-measured object based on a CHAN algorithm. The influence of non-line-of-sight errors is effectively reduced, the positioning precision isimproved, and the accuracy of a positioning result is improved.

The invention relates to a chan-weighted centroid indoor positioning method based on a Kalman filter. The method comprises the following steps: measuring the distance of a label to be positioned fromeach base station by a wireless sensor network; calculating a distance difference between a distance from the label to be positioned to other base station and a distance from the label to be positioned to a reference base station by using one of the base stations as the reference base station; inputting the distance difference data into the Kalman filter for filtering to obtain a distance difference in which a part of the noise interference is eliminated; inputting the filtered distance difference and base station coordinate information into a chan algorithm model to obtain an initial label coordinate; repeating step S1 to step S4 N times to obtain N initial label coordinates; and inputting the N initial label coordinates into a weighted centroid algorithm model to determine the final coordinate of the label to be positioned. According to the chan-weighted centroid indoor positioning method based on a Kalman filter, a Kalman filtering algorithm is used to preprocess the measured valueof the distance differences on the basis of the chan localization algorithm. The weighted centroid algorithm is used to optimize the initial positioning results. Therefore, the stability and accuracyof indoor positioning is improved.

The invention discloses a mobile station positioning design method based on Alamouti coding. The method comprises a step 1 that a sending end generates an OFDM positioning reference sequence; a step 2 that the sending end performs double-transmission single-reception Alamouti space-time coding on the generated sequence and then sends the sequence by double antennas; a step 3 that a receiving end receives two signals by a single antenna and integrates the received two signals; a step 4 that the receiving end performs maximum likelihood decoding on an integrated message in order to obtain a time-delayed positioning reference message; a step 5 that the receiving end performs cross-correlation operation to extract a time delay parameter; and a step 6 that the receiving end completes positioning by means of a Chan algorithm. The method reduces the signal reception error rate of the receiving end, improves a signal cross correlation characteristic, and optimizes wireless positioning system performance under a low signal-to-noise ratio.

The invention discloses a cellular TDOA positioning algorithm based on Taylor series expansion. The least square algorithm is used for estimating a user initial location, and then a user coordinate isobtained through a Taylor series expansion algorithm. The algorithm has good convergence performance and has the convergence speed basically same as the Taylor series expansion algorithm based on thereal coordinate. Under the condition that the amount of the baes station participating the positioning and the covariance matrix of the TDOA measurement error are same, the positioning precision of the algorithm is superior to the least square algorithm; compared with the Chan algorithm, the performance is basically same, and approaches to the Cramer-Rao lower limit. Along the increase of the base station amount and the reduction of the error, the improvement of the positioning precision of this algorithm is obviously faster than the least square algorithm.

Disclosed is a method for calculating the k-error linear complexity of a periodic sequence. According to the method, a method for constructing a stable k-error linear complexity sequence by means of the cube theory is provided firstly through the research on the linear complexity of a binary sequence the period of which is 2n, then a binary sequence the period of which is N=2<n> is provided and can be decomposed into multiple cubes which mutually disjoint, accordingly a novel method for researching the k-error linear complexity is provided, and then an error sequence for converting the calculation of the k-error linear complexity into solving of the minimum Hamming weight is provided. Based on the Games-Chan algorithm, the invention provides all counting formulas of the k-error linear complexity of the binary sequence the period of which is 2<n>, wherein the linear complexity of the binary sequence is 2<n>-m when (m,k) is fixed.

The invention discloses an electronic whiteboard experiment system and a positioning method based on infrared and ultrasonic joint positioning, and belongs to the field of wireless positioning. The experiment system mainly comprises a signal transmitting module, a signal receiving module, a signal processing module and an upper computer, the signal transmitting module integrates an infrared transmitter and an ultrasonic transmitter, and the signal receiving module integrates an infrared receiver and six ultrasonic receivers. A signal pen can generate periodic infrared and ultrasonic signals, the infrared receiver at a receiving end detects the infrared signals, the six ultrasonic receivers simultaneously start working, respectively detect respective time consumed for receiving the ultrasonic signals and transmit the signals to the signal processing module, and data corrected by a BP (back propagation) neural network are solved by the aid of a Chan algorithm to obtain a signal source. The cost of a sensor is greatly saved, the experiment system is small in size, detection data of the sensor can be timely and accurately acquired, the experiment system can serve as an experiment platform for a high-precision algorithm, and facilitating conditions are provided for research on algorithm effectiveness and the like.